Tableau study group - 3

Transcript

1. Data visualization for social sciences

2. Data source 1 Data source 2 Data source 3

3. Usually…

4. Discrete and continuous pills

5. Anatomy of a View

6. Columns and rows Here you can drag and drop Measures

   and Dimensions. The pills dropped here determine your X and Y “axes”. In case you use a continuous pill, then Tableau will create an axis. If you use a discrete pill Tableau will instead visualize a Table Header.

7. Columns and rows Same thing

8. First visualization Let’s start from the most generic visualization possible.

   Count the number of records. What does this graph represent?

9. Level of detail Mark: data point. In this case we

   have 1 data point: the sum of all records.

10. Increase level of detail Let’s increase the level of detail

    of our visualization Maybe by slicing the number of records by keywords? What does this graph represent?

11. More marks = More details Notice that the number of

    marks (data points) increased from 1 to 5.

12. More details! Nested Table Headers

13. Too much?

14. Marks pane Controls marks in the view: 1. Mark type

    2. Color 3. Detail 4. Size 5. Tooltips 6. Text Mark cards Mark type

15. 1. Mark Type Let’s see what happens if we change

    the mark (data point) type

16. 1. Mark type Automatic type: should we trust Tableau? Trusting

    Tableau all the time it’s allows to quick and easily visualize data, as long as we stick to Tableau’s built in visualization templates.

17. 2. Color An easy one. Discrete pills: different colors Continuous

    pills: color range Blue pill = discrete Green pill = continuous

18. 2. Color You can customize colors by clicking the Color

    box in the Mark pane Discrete pill example

19. 3. Details Whenever you place a dimension on the Rows

    or Columns shelf, Tableau uses the categorical members of the dimension to create table headers. The headers show how Tableau is sorting the underlying row data into specific categories. FILL THE BLANKS For example, the “___” dimension separates the “___” measure into ___ levels of detail.

20. 3. Details Drop a dimension on Detail on the Marks

    card to separate the marks in a data view according to the members of a dimension. Unlike dropping a dimension on the Rows or Columns shelf, dropping it on Detail on the Marks card is a way to show more data without changing the table structure. And it increases the level of detail too!
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24. 4. Size The Size property allows you to encode data

    by assigning different sizes to the marks in a data view. Depending on whether you use a discrete or continuous field, you will add either categorical or quantitative size encodings.

25. 4. Size Increasing the detail level

26. 4. Size To customize the size of marks, click on

    the Size mark card

27. 5. Tooltip Tooltips are details that appear when you hover

    over one or more marks in the view. Tooltips are also convenient for quickly filtering or removing a selection, or viewing underlying data. You can edit a tooltip to include both static and dynamic text. You can also modify which fields are included in a tooltip and whether you want to be able to use those fields to select marks in the view.

28. 5. Tooltip Every time we add new marks (data points)

    by adding dimensions to the View, the tooltip will automatically display the new Dimension. Let’s suppose we want to add another information on the tooltip. All we have to do is to drag and drop a measure or a dimension over the Tooltip card.

29. Notice how “Manual Version” was transformed into a Dimension (…why?)

30. 5. Tooltip Furthermore, we can also customize tooltips with custom

    text. Simply click the Tootip Mark Icon and enter your text.

31. 6. Text Pretty simply, if you drag and drop a

    dimension or a measure on the Text mark card, this will appear as a label next to each (or selected) data points (marks).

32. 6. Text What if I have a table instead of

    a graph? (Table means I have 2 table headers, on both rows and columns > I have 2 dimensions on both rows and columns) Text then corresponds to the value displayed at the intersection of each Row and Column

33. 7! Shape The Shape mark card only appears for specific

    visualization. Thanks to it, we can change the shape of our data points on the basis of measures or dimensions. Since it adds further detail to the visualization, it might add detail.

34. 7. Shape For example, plot keywords and page number. Instead

    of automatic marks, select Shape. If you click on the Shape mark card, you can change the shape. However, all data marks share the same shape: there is not enough level of detail.

35. 7. Shape One way to increase the level of detail

    is by drag and dropping one dimension or measure on the Shape mark card. Try with Sub keyword;

36. Tentative outline 1. Intro to Tableau 1. Installing the software

    2. Data sources and reshaping CSV data 3. Tinkering 2. Fundamental concepts I 1. Data – Worksheet – Dashboards – Stories 2. Dimensions and Measures 3. File formats 4. Data manipulation: join, union, blend 5. Fields operations: split, pivot, filter, clean, calculated fields 6. Tinkering 3. Tableau in action 1. Basic visualizations 2. Calculations (Ad hoc calculations, Calculation editor, Table Calculations, ) 3. Data management: extract, live, refresh 4. Tinkering 4. … 5. Dashboards and Stories

37. For questions or help, write me at: alusoli@sfu.ca THANK YOU